A small presentation of Demand Forecasting. It covers the Qualitative and Quantitative aspects of Demand Forecasting in Operations Management. Related Document File: https://www.scribd.com/doc/311049068/Demand-Forecasting

1. Presented By
Shashank Tiwari
Shashank@Tiwari.info
Demand Forecasting

2. Demand Forecasting
Role of forecasting
Planning process
Need of Forecast

3. Forecasting Methods
• Qualitative Methods
• Based on opinions
• Quantitative Methods
• Based on mathematical formulae & statistics

4. Qualitative Methods
1. Delphi Technique
2. Sales Force Opinions
3. User Expectation Method/Survey of Buyer Intentions Method

5. Delphi Technique
Delphi technique is an interactive forecasting
method which relies on panel of experts.

6. Sales Force Opinions
A method commonly used by companies for
short-term forecasts for companies sales.

7. User Expectation Method
The expectations of the buyer of the product
under forecasting is listed, accordingly the
demand of the product is ascertained.

8. Quantitative Methods
1. Moving Average Method
2. Exponential Smoothing Method
3. Regression Method

9. Moving Average Method
• Definition
• Formula
• Usage
• Restriction

10. Formula of Moving Average
Formula for computing the simple moving average
MAn = 𝑖=1
𝑛
𝐷𝑖
𝑛

11. Problem:
The ABC produce company sells and delivers food produce to restaurants and catering services
within a 100 mile radius of its warehouse. The food supply business is competitive, and the ability
to deliver orders promptly is a factor in getting new customers and keeping old ones. The manager
of the company wants to be certain enough drivers and vehicles are available to deliver orders
promptly and they have adequate inventory in stock. Therefore, the manager wants to be able to
forecast the number of orders that will occur during the next months.
From the records of delivery orders, management has accumulated the following data for the past
10 months, from which it wants to compute three and five months moving average.

12. Months Order per months
January 120
February 90
March 100
April 75
May 110
June 50
July 75
August 130
September 110
October 90

13. • Introduction
• Usage
• Reasons for being accepted widely
• Illustrations
Exponential Method

14. Calculate: Mean Absolute Deviation (M.A.D.), Mean Absolute Percentage Error
(M.A.P.E.), Mean Square Error (M.S.E.) for the following data using exponential
smoothing.
months
1 2 3 4 5 6 7 8 9 10 11 12 13
Actual
sales
240 248 254 243 251 260 249 261 268 254 265 270 ?
Example

15. • Definition
• Formula
• Usage
• Restriction
Regression Method

16. Aroma Drip coffee Inc. produces commercial coffee machines that are sold all over the world. The company’s production
facility has operated at near capacity for over a year now. Wayne Conner’s, the plant manager thinks that sales growth will
continue, and he wants to develop long range forecasts to help plan facility requirements for the next 3 years. Sales
records for the past 10 years have been compiled:
Example
Year Annual Sales
1 1000
2 1300
3 1800
4 2000
5 2000
6 2000
7 2200
8 2600
9 2900
10 3200

17. Evaluation
• Moving average method is simple to set up but is slow
• Exponential Method can take high α value for the forecast to be
responsive and low α value if the data is stable
• Regression is suitable for linear time series data and not for dynamic
data

18. Conclusion
• Quantitative Methods are easy to understand and desirable for most
the time.
• Demand Forecasting is a must for organizations to anticipate the
future & accordingly prepare for it.